YESSSS🦖🕷️ AMK Series BEAST WARS Megatron & Blackarachnia Predacons Rise! 【Thanks for the photos by 筋肉方程式】 #YOLOPARK# #beastwars# #megatron# #blackarachnia#

In RL training, a vLLM rollout engine and a Megatron trainer can run the same policy yet disagree on a token's logprob due to floating-point non-associativity. SkyRL's IsoExec combines an execution contract with a unified model, aligning rounding-sensitive execution choices across rollout and training. Bitwise parity holds across different TP, EP, and SP layouts. For Gated DeltaNet, the chunkwise-parallel recurrent algorithm makes parallel training and prefill bitwise identical to recurrent decode. Qwen3.5-35B-A3B, DAPO, 8xH100, 50 steps: logprob diff 1.6e-2 to 6.7e-7, full-step overhead 25.3% ✅ vLLM's scheduler and CUDA graphs still apply. Thanks to @JiangAlexander1 and the SkyRL team at @NovaSkyAI. 🔗

On 10/10 she's live at the @theXtakeover, Tesla Giga Texas Nicki Minaj gets three random words on live TV and turns them into bars on the spot 🎤 "Six sides, that's a hexagon / I'm the big homie, Megatron / These girls can't see me like the Yeti" — @NICKIMINAJ 🎥 @FallonTonight (The Tonight Show Starring Jimmy Fallon, NBC · June 27, 2019)

Training and rollout logprobs matched bit for bit on ROCm. The @RLKernel team integrated RL-Align/RL-Kernel with vllm-project/vime. A 200-step Qwen3-8B GRPO run on 8× @AMD MI300X recorded zero logprob mismatches between Megatron training and vLLM rollout. The strict path aligns reduction order, intermediate precision, rounding points, and math primitives across both sides. Deep dive: